Q3 2022
Product Updates

Table of Contents

RStudio

RStudio Desktop

  • Find in Files improvements: Better Find in Files experience for all platforms and particularly Windows users; now powered by regular expressions.
  • Hyperlinks: Better user experience when clicking on hyperlinks, with options to open help pages or go to a website.

RStudio Workbench

  • Session information improvements: Improved communication of session information with renamed elements, consistency across indicators, and more.

RStudio Connect

RStudio Connect

  • R is now optional: R is not required for RStudio Connect, enabling Python-only Connect servers.
  • Off-host content execution for Connect on Kubernetes: Execute content via the RStudio Job Launcher on Kubernetes.
    • Make use of native execution paradigms for underlying OS or container images.
    • In Beta; looking for feedback.

RStudio Connect

  • New logging features: Updated and redesigned content logs can now be accessed from the top Toolbar.
  • Shiny for Python: Shiny for Python applications are now fully supported.

Deprecated features

  • TensorFlow is deprecated and disabled by default. You can use another framework (Plumber, Flask, FastAPI) to create an HTTP API for your model deployment going forward.
  • Python versions 3.5 and 3.6 are now deprecated.

Package Managers

Public Package Manager

  • Binary packages for Linux: Binary versions of CRAN packages for the most popular Linux distributions, making installation much faster.

RStudio Package Manager

  • PyPI is out of beta: Use a PyPI mirror with RSPM with better performance and snapshot features.
  • Bring your own R binaries: Upload custom binary packages for internal, GitHub-only, or otherwise non-CRAN packages and make these binaries available to everyone on your team.
  • Remote CLI: Publish remotely with API tokens without having to go through an admin, making it easier to integrate securely with your existing package build process or pipeline.

RStudio in the Cloud

RStudio Cloud

  • Archive projects: Spaces that are no longer in active use can be archived.
  • Improved project search: Search by a project’s author as well as project name.

Fully-Managed Services

  • RStudio on Amazon SageMaker: Quickly and easily spin up the RStudio IDE within a Amazon SageMaker environment.
  • RStudio Workbench for Azure ML: RStudio Workbench is accessible on the Azure ML cloud platform, allowing users to access and analyze their Azure data sources.

Marketplace Offerings

  • Cloud Marketplace Offerings: Pre-built applications offered on services such as AWS Marketplace, Azure Marketplace, and Google Cloud Platform make it easier to get started with images built and tested by the vendor.
  • RStudio Workbench Launcher: In addition to Kubernetes, RStudio Workbench’s Launcher integrates with Slurm and other HPC environments.

Quarto

Quarto

Quarto is a new open-source scientific and technical publishing system.

  • “Next generation R Markdown”

  • Works with R, Python, Julia, Javascript, and many other languages

  • Works in Jupyter Notebooks and VS Code

  • Make websites, books, blogs, and more

  • Comes installed with RStudio v2022.07

 

Quarto

In July/August, we held four webinars on Quarto.

Shiny

Shiny for Python

Try out Shiny’s approachable, reactive framework in Python to create interactive web apps.

shinytest2

Test Shiny apps using the testthat framework.

library(shiny)
ui <- fluidPage(
  textInput("name", "What is your name?"),
  actionButton("greet", "Greet"),
  textOutput("greeting")
)
server <- function(input, output, session) {
  output$greeting <- renderText({
    req(input$greet)
    paste0("Hello ", isolate(input$name), "!")
  })
}
shinyApp(ui, server)

shinyuieditor

Announcing a drag-and-drop visual tool for creating and editing the UI of your Shiny app.

ShinyLive

Run Shiny for Python without a server. Share Shiny apps with a URL or deploy them to a static web hosting service.

Vetiver

Vetiver

Fluent tooling to version, share, deploy, and monitor a trained model in R or Python.

tidymodels

tidymodels

  • tidymodels v1.0.0: a collection of R packages for modeling and machine learning using tidyverse principles that makes modeling ergonomic, effective, and safe.
  • censored: a parsnip extension package for survival models.
  • tidyclust: a reimplementation of tidymodels for clustering models.

Selected Package Releases and Updates

gt

gt has significant updates with v0.6.0 and 0.7.0, including:

  • Output tables to Word documents
  • Better RTF output tables for Pharma
  • Accessibility enhancements for HTML table outputs

Pins for Python

pins removes the hassle of managing data across projects, colleagues, and teams. Now available for Python users!

board.pin_read("mtcars")
#>    mpg cyl  disp  hp drat    wt  qsec vs am gear carb
#> 0 21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
#> 1 21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
#> 2 22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
#> 3 21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
#> 4 18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2

Other Updates

RStudio is becoming Posit

rstudio::conf(2022)

Talks and materials from rstudio::conf(2022) are now available.

Workshop Materials

Stay in touch